Forecasting virus outbreaks with social media data via neural ordinary differential equations

In the midst of the covid-19 pandemic, social media data collected in real time has the potential of being an early indicator of a new epidemic wave. This possibility is explored here by using a neural ordinary differential equation (neural ODE) that is trained to predict virus outbreaks for a geogr...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Núñez, Matías, Barreiro, Nadia L., Barrio, Rafael A., Rackauckas, Christopher
Formato:	Articulo article acceptedVersion
Lenguaje:	Inglés
Publicado:	medRxiv 2021
Materias:	Redes sociales Datos recopilados Ecuación diferencial ordinaria neural Brotes de virus COVID-19 Ciencias Biomédicas
Acceso en línea:	http://rdi.uncoma.edu.ar/handle/uncomaid/16169 https://www.medrxiv.org/content/10.1101/2021.01.27.21250642v1
Aporte de:	Repositorio Institucional UNCo de Universidad Nacional del Comahue

id	I22-R178-uncomaid-16169
record_format	dspace
institution	Universidad Nacional del Comahue
institution_str	I-22
repository_str	R-178
collection	Repositorio Institucional UNCo
language	Inglés
topic	Redes sociales Datos recopilados Ecuación diferencial ordinaria neural Brotes de virus COVID-19 Ciencias Biomédicas
spellingShingle	Redes sociales Datos recopilados Ecuación diferencial ordinaria neural Brotes de virus COVID-19 Ciencias Biomédicas Núñez, Matías Barreiro, Nadia L. Barrio, Rafael A. Rackauckas, Christopher Forecasting virus outbreaks with social media data via neural ordinary differential equations
topic_facet	Redes sociales Datos recopilados Ecuación diferencial ordinaria neural Brotes de virus COVID-19 Ciencias Biomédicas
description	In the midst of the covid-19 pandemic, social media data collected in real time has the potential of being an early indicator of a new epidemic wave. This possibility is explored here by using a neural ordinary differential equation (neural ODE) that is trained to predict virus outbreaks for a geographic region. It learns from multivariate time series of signals obtained from a novel set of massive online surveys about COVID-19 symptoms. Once trained, the neural ODE is able to capture the dynamics of the interlinked local signals and accurately predict the number of new infections up to two months in advance. Moreover, it can estimate the future effects of changes in the number of infected at a given time, which can be associated with the flow of people entering or leaving a given region or, for instance, with a local vaccination campaign. This work gives compelling preliminary evidence for the predictive power of widely distributed social media surveys for public health application
format	Articulo article acceptedVersion
author	Núñez, Matías Barreiro, Nadia L. Barrio, Rafael A. Rackauckas, Christopher
author_facet	Núñez, Matías Barreiro, Nadia L. Barrio, Rafael A. Rackauckas, Christopher
author_sort	Núñez, Matías
title	Forecasting virus outbreaks with social media data via neural ordinary differential equations
title_short	Forecasting virus outbreaks with social media data via neural ordinary differential equations
title_full	Forecasting virus outbreaks with social media data via neural ordinary differential equations
title_fullStr	Forecasting virus outbreaks with social media data via neural ordinary differential equations
title_full_unstemmed	Forecasting virus outbreaks with social media data via neural ordinary differential equations
title_sort	forecasting virus outbreaks with social media data via neural ordinary differential equations
publisher	medRxiv
publishDate	2021
url	http://rdi.uncoma.edu.ar/handle/uncomaid/16169 https://www.medrxiv.org/content/10.1101/2021.01.27.21250642v1
work_keys_str_mv	AT nunezmatias forecastingvirusoutbreakswithsocialmediadatavianeuralordinarydifferentialequations AT barreironadial forecastingvirusoutbreakswithsocialmediadatavianeuralordinarydifferentialequations AT barriorafaela forecastingvirusoutbreakswithsocialmediadatavianeuralordinarydifferentialequations AT rackauckaschristopher forecastingvirusoutbreakswithsocialmediadatavianeuralordinarydifferentialequations
bdutipo_str	Repositorios
_version_	1764820506096173056

Forecasting virus outbreaks with social media data via neural ordinary differential equations

Ejemplares similares